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Unit . Descriptive Statistics with Excel TOBY Summary . This unit shows you , in a series of short videos , how to calculate descriptive statistics and make simple plots of numerical data using Excel . Prerequisite Units Unit . Introduction to Statistics for Psychological Science Unit . Managing Data Unit . Descriptive Statistics for Psychological Research 56 Descriptive Excel
Mean and Sample Standard Deviation The most popular way to define the center and spread of a single set of numerical data is the mean and standard deviation . You can also use the variance for spread , instead of the standard deviation , but then the units of measure are squared , which can be confusing ( what is a squared ?
In any event , we will be calculating the variance on the way to the standard deviation , so both of these will be available . Here are the formulae that we will use ( see Unit ) Sample Variance 31 Descriptive Statistics with Excel 57 ( Sample Standard Deviation of sin 32 Note that we will be calculating the sample values and standard deviation , so we using the formula with in the denominator . We will do the calculations on the following data ( from ) 65 54 79 57 35 14 77 45 92 Watch the video tin Median and Range The other way to define the center and spread of a single set of numerical data is the median and range ( These are both based on . The median is percentile the is the difference between the and . Note that there are two different ways to calculate a percentile . One method includes the median ( when calculating other than the ) the other method excludes the median . We use the exclusive version of , because the inclusive version has a tendency to the in the population from which the sample was taken . Warning for many spreadsheets and stats packages , the exclusive version is not the default , so you have to be ca . For the demonstration , we will use an extremely simple set of data , Watch the video 58 Descriptive Statistics with Excel
Numerical Values of Skew and Ku When center and spread are defined as the mean and standard deviation ( or variance ) there are parallel definitions of skewness and kurtosis that may be used for the shape of the data . These are also based on the method of moments . The formulae for these are quite complicated , so we will be jumping directly to functions . Note that a perfect bell curve , known as the normal distribution , has skew and kurtosis . A new set of ( random ) data will be used for this demonstration . Watch the video Simple Frequency Plots ( of Numerical Data The more general approach to skew and kurtosis is to make a plot of the data and simply look for asymmetry ( skew ) and peakedness ( kurtosis ) As will be shown , in some cases , the data must be binned before being plotted . Watch the video Descriptive Statistics with Excel 59